MapR Adds Complete Apache Spark Stack to its Distribution for Hadoop

MapR
Technologies, Inc., provider of the top-ranked distribution for
Apache Hadoop, today announced a strategic partnership with Databricks
and the addition of the complete Apache Spark technology stack to the
MapR Distribution. The Spark in-memory processing framework provides
speed, programming ease and real-time processing advantages.

"It has become clear that Apache Spark offers a combination of
high-performance, in-memory data processing and multiple computation
models that is well suited to serving as the basis of next-generation
data processing platforms," commented Matt Aslett, research director,
data platforms and analytics, 451 Research. “MapR's support for the
complete Spark stack, combined with its partnership with Databricks,
should give Hadoop users the confidence to start developing applications
to take advantage of Spark's performance and flexibility."

Organizations are looking for easier and faster ways to derive value
from big data. Spark improves both performance and developer
productivity:

Performance. Spark provides a general-purpose execution
framework with in-memory pipelining to speed up end-to-end application
performance. For many applications, this results in a 5-100x
performance improvement.

Developer productivity. Spark jobs can require as little as 1/5th
the number of lines of code. Spark provides a simple programming
abstraction allowing developers to design applications as operations
on data collections (known as RDDs, or Resilient Distributed Dataset).
Developers can build these applications in multiple programming
languages, including Java, Scala and Python, and the same code can be
reused across batch, interactive and streaming applications.

Many organizations are currently running Spark in production in their
MapR environments. Their Spark-based applications benefit from the
enterprise-grade dependability and performance of the MapR Distribution,
and from the ability to process real-time operational data due to MapR’s
Direct Access NFS interface.

With the inclusion of the complete Spark stack in the MapR Distribution,
MapR customers can obtain 24x7 support for all projects in the Spark
stack. In addition, MapR and Databricks are joining forces to drive the
roadmap and accelerate innovation on these projects. This will benefit
MapR customers and the broader Hadoop community over the coming years,
starting with the upcoming release of Apache Spark 1.0.

CIO, CTO & Developer Resources

"As the driving force behind Spark, Databricks is thrilled to enter into
such a strategic partnership with MapR," said Ion Stoica, CEO of
Databricks. "We are looking forward to combining MapR's enterprise-grade
dependability and performance with Spark, the next generation big data
engine, to enable enterprises to unlock deeper insights from their data,
faster.”

“The open source community is developing tremendous technology
innovations at a rapid pace,” said John Schroeder, CEO and cofounder,
MapR Technologies. “MapR provides a future-proof investment for our
customers with the most open distribution to give them flexibility to
pick the right solution with the widest range of compute frameworks and
libraries.”

The Spark stack includes five unique Apache open source projects. With
the introduction of the complete Spark stack, the MapR Distribution now
includes more than 20 Apache open source projects. These projects
support a wide range of use cases, including batch, interactive,
streaming, graph and machine leaning. MapR is the only distribution with
a monthly release cadence for Apache open source projects. This enables
customers to upgrade components of the distribution without upgrading
the entire cluster. It also enables faster adoption of open source
innovation while reducing the risk of disruption to the production
cluster services.

About MapR Technologies

MapR
delivers on the promise of Hadoop with a proven, enterprise-grade
platform that supports a broad set of mission-critical and real-time
production uses. MapR brings unprecedented dependability, ease-of-use
and world-record speed to Hadoop, NoSQL, database and streaming
applications in one unified distribution for Hadoop. MapR is used by
more than 500 customers across financial services, retail, media,
healthcare, manufacturing, telecommunications and government
organizations as well as by leading Fortune 100 and Web 2.0 companies.
Amazon, Cisco, Google and HP are part of the broad MapR partner
ecosystem. Investors include Lightspeed Venture Partners, Mayfield Fund,
NEA, and Redpoint Ventures. MapR is based in San Jose, CA. Connect with
MapR on Facebook,
LinkedIn,
and Twitter.

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